GAN-DIRNet:A Novel Deformable Image Registration Approach for Multimodal Histological Images

Multi-modal histological image registration tasks pose significant challenges due to tissue staining operations causing partial loss and folding of tissue.Convolutional neural network(CNN)and generative adversarial network(GAN)are pivotal inmedical image registration.However,existing methods often struggle with severe interference and deformation,as seen in histological images of conditions like Cushing’s disease.We argue that the failure of current approaches lies in underutilizing the feature extraction capability of the discriminator inGAN.In this study,we propose a novel multi-modal registration approach GAN-DIRNet based on GAN for deformable histological image registration.To begin with,the discriminators of two GANs are embedded as a new dual parallel feature extraction module into the unsupervised registration networks,characterized by implicitly extracting feature descriptors of specific modalities.Additionally,modal feature description layers and registration layers collaborate in unsupervised optimization,facilitating faster convergence and more precise results.Lastly,experiments and evaluations were conducted on the registration of the Mixed National Institute of Standards and Technology database(MNIST),eight publicly available datasets of histological sections and the Clustering-Registration-Classification-Segmentation(CRCS)dataset on the Cushing’s disease.Experimental results demonstrate that our proposed GAN-DIRNet method surpasses existing approaches like DIRNet in terms of both registration accuracy and time efficiency,while also exhibiting robustness across different image types.

Pervasive Attentive Neural Network for Intelligent Image Classification Based on N-CDE’s

The utilization of visual attention enhances the performance of image classification tasks.Previous attentionbased models have demonstrated notable performance,but many of these models exhibit reduced accuracy when confronted with inter-class and intra-class similarities and differences.Neural-Controlled Differential Equations(N-CDE’s)and Neural Ordinary Differential Equations(NODE’s)are extensively utilized within this context.NCDE’s possesses the capacity to effectively illustrate both inter-class and intra-class similarities and differences with enhanced clarity.To this end,an attentive neural network has been proposed to generate attention maps,which uses two different types of N-CDE’s,one for adopting hidden layers and the other to generate attention values.Two distinct attention techniques are implemented including time-wise attention,also referred to as bottom N-CDE’s;and element-wise attention,called topN-CDE’s.Additionally,a trainingmethodology is proposed to guarantee that the training problem is sufficiently presented.Two classification tasks including fine-grained visual classification andmulti-label classification,are utilized to evaluate the proposedmodel.The proposedmethodology is employed on five publicly available datasets,including CUB-200-2011,ImageNet-1K,PASCAL VOC 2007,PASCAL VOC 2012,and MS COCO.The obtained visualizations have demonstrated that N-CDE’s are better appropriate for attention-based activities in comparison to conventional NODE’s.

Appendicitis combined with Meckel’s diverticulum obstruction, perforation, and inflammation in children: Three case reports

BACKGROUND Meckel’s diverticulum is a common congenital malformation of the small intestine,with the three most common complications being obstruction,per-foration,and inflammation.To date,only a few cases have been reported world-wide.In children,the clinical symptoms are similar to appendicitis.As most of the imaging features are nonspecific,the preoperative diagnosis is not precise.In addition,the clinical characteristics are highly similar to pediatric acute appendicitis,thus special attention is necessary to distinguish Meckel’s diver-ticulum from pediatric appendicitis.Patients with poor disease control should undergo laparoscopic exploration to avoid serious complications,including intestinal necrosis,intestinal perforation and gastrointestinal bleeding.CASE SUMMARY This report presents three cases of appendicitis in children combined with intestinal obstruction,which was caused by fibrous bands(ligaments)arising from the top part of Meckel's diverticulum,diverticular perforation,and diver-ticular inflammation.All three patients,aged 11-12 years,had acute appendicitis as their initial clinical presentation.All were treated by laparoscopic surgery with a favorable outcome.A complete dataset including clinical presentation,dia-gnostic imaging,surgical information,and histopathologic findings was also provided.CONCLUSION Preoperative diagnosis of Meckel’s diverticulum and its complications is challenging because its clinical signs and complications are similar to those of appendicitis in children.Laparoscopy combined with laparotomy is useful for diagnosis and treatment.

Relationship between Authoritative Parenting Style and Preschool Children’s Emotion Regulation:A Moderated Mediation Model

An authoritative parenting style has been shown to promote children’s emotion regulation in European-American family studies.However,little is known about how sleep problems and the child’s sibling status in Chinese families affect this relationship.Based on family system theory,this study attempts to better understand the relationship between authoritative parenting style and emotion regulation.Mothers of preschool children in Chinese kindergartens completed questionnaires about their children’s sleep habits,their authoritative parenting styles,and children’s emotion regulation.A total of 531 children participated in this study.Results showed that authoritative parenting was positively associated with emotional regulation.Sleep problems mediated the effects of authoritative parenting style on emotion regulation.The child’s sibling status moderated the mediating effects of sleep problems in authoritative parenting and emotion regulation relationships.Specifically,the relationship between the authoritative parenting style and sleep problems was significant for only children,while birth order had no significant influence on the authoritative parenting style and sleep problems in two-child families.These findings suggest that a lowauthoritative parenting style predicts low emotion regulation through sleep problems,and this depends on the child’s sibling status,indicating that children without siblings may impair emotion regulation due to increased sleep problems.

A Spectral Convolutional Neural Network Model Based on Adaptive Fick’s Law for Hyperspectral Image Classification

Hyperspectral image classification stands as a pivotal task within the field of remote sensing,yet achieving highprecision classification remains a significant challenge.In response to this challenge,a Spectral Convolutional Neural Network model based on Adaptive Fick’s Law Algorithm(AFLA-SCNN)is proposed.The Adaptive Fick’s Law Algorithm(AFLA)constitutes a novel metaheuristic algorithm introduced herein,encompassing three new strategies:Adaptive weight factor,Gaussian mutation,and probability update policy.With adaptive weight factor,the algorithmcan adjust theweights according to the change in the number of iterations to improve the performance of the algorithm.Gaussianmutation helps the algorithm avoid falling into local optimal solutions and improves the searchability of the algorithm.The probability update strategy helps to improve the exploitability and adaptability of the algorithm.Within the AFLA-SCNN model,AFLA is employed to optimize two hyperparameters in the SCNN model,namely,“numEpochs”and“miniBatchSize”,to attain their optimal values.AFLA’s performance is initially validated across 28 functions in 10D,30D,and 50D for CEC2013 and 29 functions in 10D,30D,and 50D for CEC2017.Experimental results indicate AFLA’s marked performance superiority over nine other prominent optimization algorithms.Subsequently,the AFLA-SCNN model was compared with the Spectral Convolutional Neural Network model based on Fick’s Law Algorithm(FLA-SCNN),Spectral Convolutional Neural Network model based on Harris Hawks Optimization(HHO-SCNN),Spectral Convolutional Neural Network model based onDifferential Evolution(DE-SCNN),SpectralConvolutionalNeuralNetwork(SCNN)model,and SupportVector Machines(SVM)model using the Indian Pines dataset and PaviaUniversity dataset.The experimental results show that the AFLA-SCNN model outperforms other models in terms of Accuracy,Precision,Recall,and F1-score on Indian Pines and Pavia University.Among them,the Accuracy of the AFLA-SCNN model on Indian Pines reached 99.875%,and the Accuracy on PaviaUniversity reached 98.022%.In conclusion,our proposed AFLA-SCNN model is deemed to significantly enhance the precision of hyperspectral image classification.

Design of a Landscape Device for Children from the Perspective of Embodied Cognition in the New Era

In recent years,embodied cognition has ushered in a new research upsurge in the academic field,and has become a hot topic in the field of cognitive psychology.In this paper,from the perspective of embodied cognition,the interaction ways of a landscape device for children were discussed to achieve a more real and harmonious interaction between children and scenes.The research data of embodied cognition used by children was analyzed,and the drawbacks and breakthrough points of current landscape devices for children were discussed.The core characteristics of children’s growth period were extracted to establish children’s interaction model and summarize the interactive design methods of landscape devices for children.Embodied cognition has become the most intuitive way for children to know and understand the environment,and plays a pivotal role in children’s growth.Based on embodied cognition principle and interactive behavior mode,the interactive design of a landscape device for children was studied,and three interactive design modes,including simple and convenient interaction mode,multi-sensory interaction mode and game natural interaction mode were summarized.On the basis of this research,relevant design practice and research were carried out to bring a new vision to the design of children’s landscape.

Recent progress in the applications of presynaptic dopaminergic positron emission tomography imaging in parkinsonism

Nowadays,presynaptic dopaminergic positron emission tomography,which assesses deficiencies in dopamine synthesis,storage,and transport,is widely utilized for early diagnosis and differential diagnosis of parkinsonism.This review provides a comprehensive summary of the latest developments in the application of presynaptic dopaminergic positron emission tomography imaging in disorders that manifest parkinsonism.We conducted a thorough literature search using reputable databases such as PubMed and Web of Science.Selection criteria involved identifying peer-reviewed articles published within the last 5 years,with emphasis on their relevance to clinical applications.The findings from these studies highlight that presynaptic dopaminergic positron emission tomography has demonstrated potential not only in diagnosing and differentiating various Parkinsonian conditions but also in assessing disease severity and predicting prognosis.Moreover,when employed in conjunction with other imaging modalities and advanced analytical methods,presynaptic dopaminergic positron emission tomography has been validated as a reliable in vivo biomarker.This validation extends to screening and exploring potential neuropathological mechanisms associated with dopaminergic depletion.In summary,the insights gained from interpreting these studies are crucial for enhancing the effectiveness of preclinical investigations and clinical trials,ultimately advancing toward the goals of neuroregeneration in parkinsonian disorders.

On Translation of Children’s Literature Based on Reception Aesthetics:A Case Study of The Secret Garden

Grounded in reader-centered theories,Reception Aesthetics prioritizes the active engagement and acceptance of target readers.This study examines the translation of children’s literature through the lens of Reception Aesthetics,using Li Wenjun’s rendition of The Secret Garden as a case study.The objective is to scrutinize various aspects of the translation-including vocabulary,syntax,rhetorical devices,and cultural nuances-and to discern how the adaptation and application of diverse translation strategies cater to the aesthetic expectations.

Reflections on Conducting Kindergarten Language Education Activities Based on Children’s Literature

In early childhood education,language education is a crucial component,yet in kindergarten teaching,there often exists issues such as“emphasis on knowledge and neglect of practice.”To address this problem,teachers need to incorporate children’s literature in a reasonable manner to create a conducive environment for language education for young children.This article analyzes and discusses the significance of integrating children’s literature into kindergarten language education activities,and proposes strategies for addressing the current issues in kindergarten language education activities and conducting them based on children’s literature.

Research on the Influence of Family Education on Children’s Behavioral Habits

Under the background of the all-round deepening of quality education,the cultivation of comprehensive quality has become the main theme of contemporary education reform.Good behavior and habits are of great significance to children’s future learning,growth,and development.Through literature review and other methods,this paper analyzes the current situation of children’s family education and the influence of family education on the cultivation of children’s behavioral habits and provides some strategies for cultivating children’s good behavioral habits in family education.

The Market Development of Children’s Go Training and the Difficulty and Countermeasure Analysis of Go Training

The children’s Go training market is experiencing vigorous growth but also faces several challenges.As the importance of Go in cultural education increases,the market expands,with growing demand and involvement from training and educational institutions.However,the market encounters difficulties such as a shortage of high-quality Go coaches,uniformity in training content and methods,and high training costs.To address these issues,measures can be taken to strengthen the team of Go coaches,diversify training content and methods,and optimize the training cost structure,thereby promoting the healthy development of the children’s Go training market.

A Study of Health Prescribing for Children with Tourette’s Disorders in Children’s Health Education Specialty Care Clinics

Objective:This study designs and implements the health prescription of children’s health education specialized nursing clinic based on the physical and mental characteristics of children with Tourette’s syndrome.Methods:Applying the evidence-based nursing model and nursing intervention theory based on the survey research by searching China Knowledge Network,Wanfang Database and Wipro Chinese Science and Technology Journal Database,the study collected the literature on the health prescription intervention research in children’s Tourette’s disorders health education in children’s health education of specialized nursing outpatient clinic for review and combined with the specialty characteristics to formulate“Children’s Tourette’s Disorder Health Education Prescription.”Results:Tourette’s syndrome in children is a common pediatric neurological disorder,mainly manifested as involuntary,rapid and repeated muscle twitching and vocal tics,which brings serious psychological pressure and life disturbance to the affected children.Conclusion:For children with Tourette’s syndrome,healthcare professionals should give enough care and understanding to the children and their parents,provide timely and effective health education to them,help them improve their bad behavioral habits,establish correct cognitive attitudes,enhance self-confidence,improve patient compliance,reduce the frequency of recurrence,reduce the incidence of complications and promote children’s physical and mental health development.

Research on Children’s Game Activity Design Strategies Based on Embodied Cognition Theory

Edutainment,in the kindergarten education stage,emphasizes the game as the basic activity and combines the content of education with the form of the game,thus it also forms the educational method of gamification teaching.Through investigation and analysis,it is found that the current kindergarten game activity design has the problem of improper combination of educational content and game form.The current kindergarten game activity design has problems such as stereotypes,children’s lack of active learning opportunities in activities,teachers’insufficient theoretical understanding,inappropriate teacher guidance methods,and so on.Embodied cognition theory attaches importance to the important role of the body in the development of cognition,provides new guidance for classroom teaching,and opens up a new path for classroom teaching reform.Based on the perspective of embodied cognition theory,the concept of body and mind integration should be adhered to in kindergarten teaching with games as the basic activity,experiential teaching situation should be created,children’s subjective experience should be respected,and games and interactions should be designed to promote children’s physical and mental participation,thus laying a foundation for the realization of children’s individual freedom,autonomy,and all-round development.Therefore,this paper aims at the existing problems in the current kindergarten gamification teaching and discusses the design strategy of children’s game activities based on embodied cognition theory.

Analysis of the Tragic Female Images in Eugene O'Neill's Plays

Ruth and Mary are two heroines in Eugene O'Neill's plays Beyond the Horizon, and Long Day's Journey into Night. They have some similarities: when they are young, they are beautiful, native and full of hope towards the future life, but both make wrong choices; in the following years, both suffer a lot from these wrong choices, and feel regretful. This paper tries to explore these two tragic female images.

基于轻量化YOLOX-S与多阈值分割的矿山遥感图像去噪算法

矿山遥感图像普遍存在大量的噪点,给后续图像分析和处理带来了很大困难。提出了一种基于轻量化目标检测模型YOLOX-S和多阈值分割的矿山遥感图像去噪算法。首先使用YOLOX-S模型对矿山遥感图像进行目标检测,得到矿山目标的位置信息。然后针对矿山目标的特点,设计了一种多阈值分割方法消除图像中的噪声点。通过将图像分为若干个子区域,并对每个子区域采用不同的阈值进行二值化处理,最终将各子区域的二值化结果合并得到去噪后的图像。试验结果表明:该算法能够有效地去除矿山遥感图像中的噪声点,并且在保留目标特征的同时,大幅提升了图像质量。此外,由于采用了轻量化模型和多阈值分割算法,使得该算法具有较快的处理速度和较低的计算成本,适用于大规模图像数据的处理任务。

常规磁共振序列联合ASL在儿童局灶性皮层发育不良中的诊断价值

目的:分析局灶性皮质发育不良(FCD)患儿常规MRI序列及动脉自旋标记(ASL)的扫描图像,探讨其对FCD的诊断价值。方法:回顾性分析2021年7月至2023年8月经病理确诊为FCD的30例患儿MRI图像,包括常规MRI T1WI、T2WI、FLAIR序列及ASL扫描序列,分析FCD不同分型的MRI影像学特点,并对ASL图像经后处理获得病变区脑血流量(CBF)值及同水平对侧正常区CBF值进行比较,计算常规MRI序列及常规MRI序列联合ASL扫描序列诊断FCD的准确率。结果:常规MRI序列评估结果阳性21例,准确率为70%。FCD I型6例,主要表现为局部脑组织容积偏小,灰白质模糊;FCD II型7例,以皮层增厚,皮层及皮层下片状T1WI稍低信号,T2WI高信号,T2-FAIR高信号为主,典型者呈Tansmantle征;FCD III型8例,合并海马硬化、肿瘤、血管畸形。常规MRI序列及ASL联合扫描示27例灌注异常,准确率为90%,27例病灶区CBF值[(48.15±6.00)mL/(100g·min)]低于对侧正常区CBF值[(79.66±6.53)mL/(100g·min)](t=18.458,P<0.001)。结论:不同分型FCD具有特征性影像表现,但I型病灶较隐匿,II型典型表现出现概率少,容易漏诊,III型容易被合并病灶掩盖,ASL扫描序列有助于FCD病灶的检出及定位,与常规MRI序列联合检查可进一步提高诊断FCD的准确率。

基于MRI影像组学构建PD-1/PD-L1抑制剂治疗dMMR/MSI-H直肠癌疗效的预测模型

目的:探讨MRI影像组学模型在程序性细胞死亡蛋白-1(PD-1)/程序性细胞死亡-配体1(PD-L1)抑制剂联合全程新辅助治疗(TNT)局部进展期直肠癌(LARC)的疗效预测价值。方法:收集河南中医药大学第一附属医院PD-1/PD-L1抑制剂联合TNT治疗的80例错配修复基因缺陷(dMMR)/微卫星高度不稳定(MSI-H)基因型中低位LARC患者的临床和影像资料。将入组患者按7∶3比例分为训练集和测试集,提取影像组学特征,从中筛选并构建影像组学模型。描绘影像组学模型的Rad-score与病理金标准之间的受试者工作特征(ROC)曲线,计算曲线下面积(AUC),并评价模型的诊断效能。采用决策曲线分析(DCA)计算风险阈值的范围,并评估临床获益情况。收集湖南省人民医院25例dMMR/MSI-H基因型LARC患者的影像资料作为外部验证集。结果:训练集、测试集及外部验证集三者之间的临床特征无统计学差异(P>0.05)。经过降维处理、t检验及一致性检验以及LASSO交叉验证后,筛选出一阶偏度特征和体积2个特征构建影像组学模型。训练集、测试集和外部验证集的影像组学预测模型ROC曲线的AUC、灵敏度、特异度、阳性预测值和阴性预测值分别为0.920、97.1%、85.7%、91.9%、94.7%;0.885、80.0%、88.9%、92.3%、72.7%;0.875、87.5%、88.9%、93.3%、80.0%。DCA曲线显示,当风险阈值范围为0%~82%时,采用影像组学模型预测LARC患者为病理完全缓解(pCR)的获益大于将所有患者都视为pCR或者无病理完全缓解(npCR)。结论:基于MRI影像组学构建的dMMR/MSI-H型局部进展期直肠癌PD-1/PD-L1抑制剂联合全程新辅助放化疗疗效预测模型,有较大潜力为不同基因分型的直肠癌患者制定个体化治疗策略提供量化依据。

Detection of Alzheimer’s disease onset using MRI and PET neuroimaging:longitudinal data analysis and machine learning

The scientists are dedicated to studying the detection of Alzheimer’s disease onset to find a cure, or at the very least, medication that can slow the progression of the disease. This article explores the effectiveness of longitudinal data analysis, artificial intelligence, and machine learning approaches based on magnetic resonance imaging and positron emission tomography neuroimaging modalities for progression estimation and the detection of Alzheimer’s disease onset. The significance of feature extraction in highly complex neuroimaging data, identification of vulnerable brain regions, and the determination of the threshold values for plaques, tangles, and neurodegeneration of these regions will extensively be evaluated. Developing automated methods to improve the aforementioned research areas would enable specialists to determine the progression of the disease and find the link between the biomarkers and more accurate detection of Alzheimer’s disease onset.

Magnetic resonance imaging in children and adolescents with chronic inflammatory bowel disease

Inflammatory bowel diseases(IBD) represent challenges, both from a diagnostic, and therapeutic point of view. Deep-seated anatomic structures are difficult to assess by ultrasound technique alone. As radiation-free alternative cross-sectional imaging method, magnetic resonance imaging of the intestinal structures is costly and time-consuming. Examination of pediatric patients imply additional considerations: reduction of body motions in younger children and consideration of the most appropriate preparation, and examination technique. The demanding Sellink technique is the only means for appropriately distending the lesser intestine in order to detect small bowel strictures. Oral intake of contrast medium(CM) alone shows its limitations regarding distensibility. The need for intravenous contrast media application needs to be considered, too. Active inflammation of both intestinal wall, and mesentery can be demonstrated accurately. Nevertheless, viable alternatives to CM application is desirable, considering non-negligible adverse reactions. Recent data suggest diffusion weighted imaging might fill this diagnostic gap. Irrespective of sequence technique chosen, bowel movement remains a major obstacle. Antispasmolytics in their function as smooth muscle relaxants help in improving image quality, however, their use in children might be off-label. Optimal preparation for the examination and appropriate imaging technique allow for diagnosing typical patterns of changes in IBD, such as bowel wall thickening, ulcers, mural stratification, strictures, creeping fat, and comb sign, and lymphadenopathy. The article gives a detailed overview of current significance of magnetic resonance imaging pediatric patients suffering from IBD, considering indications, limitations, and safety aspects.

Image Segmentation of Brain MR Images Using Otsu’s Based Hybrid WCMFO Algorithm

In this study,a novel hybrid Water Cycle Moth-Flame Optimization(WCMFO)algorithm is proposed for multilevel thresholding brain image segmentation in Magnetic Resonance(MR)image slices.WCMFO constitutes a hybrid between the two techniques,comprising the water cycle and moth-flame optimization algorithms.The optimal thresholds are obtained by maximizing the between class variance(Otsu’s function)of the image.To test the performance of threshold searching process,the proposed algorithm has been evaluated on standard benchmark of ten axial T2-weighted brain MR images for image segmentation.The experimental outcomes infer that it produces better optimal threshold values at a greater and quicker convergence rate.In contrast to other state-of-the-art methods,namely Adaptive Wind Driven Optimization(AWDO),Adaptive Bacterial Foraging(ABF)and Particle Swarm Optimization(PSO),the proposed algorithm has been found to be better at producing the best objective function,Peak Signal-to-Noise Ratio(PSNR),Standard Deviation(STD)and lower computational time values.Further,it was observed thatthe segmented image gives greater detail when the threshold level increases.Moreover,the statistical test result confirms that the best and mean values are almost zero and the average difference between best and mean value 1.86 is obtained through the 30 executions of the proposed algorithm.Thus,these images will lead to better segments of gray,white and cerebrospinal fluid that enable better clinical choices and diagnoses using a proposed algorithm.